D
Dmitry I. Ignatov
Researcher at National Research University – Higher School of Economics
Publications - 115
Citations - 1600
Dmitry I. Ignatov is an academic researcher from National Research University – Higher School of Economics. The author has contributed to research in topics: Recommender system & Formal concept analysis. The author has an hindex of 20, co-authored 104 publications receiving 1396 citations. Previous affiliations of Dmitry I. Ignatov include Huawei & Russian Academy of Sciences.
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Journal ArticleDOI
Review: Formal concept analysis in knowledge processing: A survey on applications
TL;DR: This second part of a large survey paper analyzes recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA and uses the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community.
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Review: Formal Concept Analysis in knowledge processing: A survey on models and techniques
Jonas Poelmans,Jonas Poelmans,Sergei O. Kuznetsov,Dmitry I. Ignatov,Guido Dedene,Guido Dedene +5 more
TL;DR: This is the first part of a large survey paper in which recent literature on Formal Concept Analysis (FCA) is analyzed and an extensive overview of the papers published between 2003 and 2011 on developing FCA-based methods for knowledge processing is given.
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Triadic Formal Concept Analysis and triclustering: searching for optimal patterns
TL;DR: This paper presents several definitions of “optimal patterns” in triadic data and results of experimental comparison of five triclustering algorithms on real-world and synthetic datasets and leads to a clear strategy for choosing a solution at a given dataset guided by the principle of Pareto-optimality.
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Fuzzy and rough formal concept analysis: a survey
TL;DR: This paper applied traditional FCA as a text-mining instrument to 1072 papers mentioning FCA in the abstract and transformed them into concept lattices, which were used to analyze and explore the most prominent research topics within the FCA with fuzzy attributes and rough FCA research communities.
Proceedings ArticleDOI
Concept-Based Biclustering for Internet Advertisement
TL;DR: The paper contains experimental results on applying the proposed algorithm to contextual Internet advertisement data in comparison with some FCA algorithms and additional results on so-called morphological metarules for term recommendation task on the same data.